ShopRecog: Mobile application for shop recognition with text to speech

This report documents the development and implementation of the "ShopRecog" mobile application, designed to address the unique needs of visually impaired individuals by leveraging advanced technologies such as machine learning, text recognition, and API integrations. The application provid...

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Main Author: Khoo, Zi Yi
Format: Final Year Project / Dissertation / Thesis
Published: 2024
Subjects:
Online Access:http://eprints.utar.edu.my/6643/
http://eprints.utar.edu.my/6643/1/fyp_CS_2024_KZY.pdf
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author Khoo, Zi Yi
author_facet Khoo, Zi Yi
author_sort Khoo, Zi Yi
building UTAR Institutional Repository
collection Online Access
description This report documents the development and implementation of the "ShopRecog" mobile application, designed to address the unique needs of visually impaired individuals by leveraging advanced technologies such as machine learning, text recognition, and API integrations. The application provides real-time shop recognition, interactive speech-to-text functionality, comprehensive shop information retrieval, AI-generated summaries, and navigation assistance, all tailored for a seamless and user-friendly experience. Through rigorous testing, performance evaluation, and user feedback, the application demonstrates its effectiveness in enhancing independence, information access, and navigation support for visually impaired users. The report concludes with recommendations for continuous improvement, localization, adherence to accessibility standards, user feedback integration, and collaboration for further impact and innovation in assistive technologies.
first_indexed 2025-11-15T19:43:12Z
format Final Year Project / Dissertation / Thesis
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institution Universiti Tunku Abdul Rahman
institution_category Local University
last_indexed 2025-11-15T19:43:12Z
publishDate 2024
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spelling utar-66432024-10-23T05:58:07Z ShopRecog: Mobile application for shop recognition with text to speech Khoo, Zi Yi T Technology (General) TD Environmental technology. Sanitary engineering This report documents the development and implementation of the "ShopRecog" mobile application, designed to address the unique needs of visually impaired individuals by leveraging advanced technologies such as machine learning, text recognition, and API integrations. The application provides real-time shop recognition, interactive speech-to-text functionality, comprehensive shop information retrieval, AI-generated summaries, and navigation assistance, all tailored for a seamless and user-friendly experience. Through rigorous testing, performance evaluation, and user feedback, the application demonstrates its effectiveness in enhancing independence, information access, and navigation support for visually impaired users. The report concludes with recommendations for continuous improvement, localization, adherence to accessibility standards, user feedback integration, and collaboration for further impact and innovation in assistive technologies. 2024-01 Final Year Project / Dissertation / Thesis NonPeerReviewed application/pdf http://eprints.utar.edu.my/6643/1/fyp_CS_2024_KZY.pdf Khoo, Zi Yi (2024) ShopRecog: Mobile application for shop recognition with text to speech. Final Year Project, UTAR. http://eprints.utar.edu.my/6643/
spellingShingle T Technology (General)
TD Environmental technology. Sanitary engineering
Khoo, Zi Yi
ShopRecog: Mobile application for shop recognition with text to speech
title ShopRecog: Mobile application for shop recognition with text to speech
title_full ShopRecog: Mobile application for shop recognition with text to speech
title_fullStr ShopRecog: Mobile application for shop recognition with text to speech
title_full_unstemmed ShopRecog: Mobile application for shop recognition with text to speech
title_short ShopRecog: Mobile application for shop recognition with text to speech
title_sort shoprecog: mobile application for shop recognition with text to speech
topic T Technology (General)
TD Environmental technology. Sanitary engineering
url http://eprints.utar.edu.my/6643/
http://eprints.utar.edu.my/6643/1/fyp_CS_2024_KZY.pdf